In-car navigation apparatus

ABSTRACT

An in-car navigation apparatus capable of searching an optimal or a quasi-optimal route always, and further capable of shortening the waiting time until a route is obtained, has an operating section which receives a starting point, a destination and searching conditions for searching from a handling section to read digital map data to be used for searching from the map database section of the apparatus. The operating section holds a plurality of weighting factors of each heuristic term to be used in an evaluation function or computing formulae to be used for the evaluation function, and searches an optimal or a quasi-optimal route by selecting an appropriate one in accordance with the road conditions and the searching conditions of the map data read in when searching is performed.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates to an in-car navigation apparatus for searchingan optimal route between two appointed points on a road map, the digitaldata of which have a hierarchy construction, by means of a heuristicalgorithm.

2. Description of the Prior Art

FIG. 9 is a block diagram showing the construction of a conventionalin-car navigation apparatus disclosed in, for example Japanese PublishedUnexamined Patent Application No. 131592/'94 (Tokkai-Hei 6-131592). Inthe figure, reference numeral 1 denotes a position detecting section fordetecting the present position of a car. Reference numeral 2 denotes amap database section using a medium capable of storing information withlarge capacity such as picture data for displaying a map, digital mapdata for searching, etc.; for example a CD-ROM can be used as themedium. Reference numeral 3 denotes a handling section with which a userinputs a destination, a condition for searching, a condition fordisplaying a picture, or the like. Reference numeral 4 denotes anoperating section for searching an optimal route from a starting pointto a destination both of which are set by a user with the handlingsection 3 on the digital map data read in from the map database section2 in conformity with a set condition. Reference numeral 5 denotes adisplaying section for displaying picture data at a necessary area whichare read in from the map database section 2, for drawing a car mark at aposition corresponding to the present position of a car detected by theposition detecting section 1 in the displayed picture, and fordisplaying a route mark along a route searched by the operating section4; the displaying section 5 using a display such as a liquid crystaldisplay, or the like.

In operation, such an in-car navigation apparatus is constructed tosearch an optimal route from an appointed starting point to an appointeddestination for guiding a car when a user requires the optimal route byappointing the starting point and the destination for searching theroute with the handling section 3 while referring to a map displayed onthe screen of the displaying section 5. The digital map data stored inthe map database section 2 and to be used for route-searching iscomposed of characteristic points on roads called nodes (such asintersections, route-changing points and the like) and links connectingeach node.

The operating section 4 searches a route between the starting point andthe destination set on the digital map data stored in the map databasesection 2, and pursues links connected to a link including the node s ofthe starting point successively from the node s until it arrives at thenode o of the destination by gradually expanding the range of searching.During this operation, the evaluation functions of each node being inthe sphere searched yet are computed to be pursued from a node havingsmaller evaluation functions in order.

If algorithms in which the range of searching is expanded in alldirections equivalently such as a transverse type searching method,Dijkstra method or the like are used for computing the evaluationfunctions, the range of searching becomes a circle the center of whichis the node s of a starting point, and the opposite directions arewidely included in the circle, which increases the computation timerequired for searching. Accordingly, a method for decreasing thesearching time by preferentially searching areas toward a destination bymeans of a heuristic algorithm such as algorithm A disclosed in, forexample an article by Hart and Nilsson titled "A Formal Basis for theHeuristic Determination of Minimum Cost Paths", IEEE Transactions ofSystems Science and Cybernetics, Vol. SSC-4, No. 2, pp. 100-107, isused.

In the algorithm A, an evaluation function f(n) at a node n is obtainedin conformity with the following formula.

    f(n)=g(n)+h(n)                                             (1)

where g(n) is the cost of an optimal route from a node s of a startingpoint to the node N, and h(n) is called a heuristic term and is theestimated cost from the node n to the node o of a destination.

In case of searching a route having the shortest length, the cost g(n)can be obtained as the length of a route from the node s of a startingpoint to the node n, namely the sum of all links included in the route.

If it is ensured that the heuristic term h(n) is smaller than the actualminimum route cost from the node n to the node o of a destination, it isensured that the minimum route can be searched by using the algorithm A;the algorithm A in this case is especially called algorithm A*. In thiscase, since the length of a route connecting two points is always longerthan the length of a straight line connecting the two points, theheuristic term h(n) is ordinarily obtained as the length of a straightline connecting the node n and the node o of a destination.

In the searching using the algorithm A*, the nearer the heuristic termh(n) is to the actual cost from the node n to the node o of adestination, the better the efficiency of the searching is and theshorter the time for the searching becomes. Now, a weighting factor k ofa heuristic term h(n) given by the following formula is introduced.

    k=(the actual cost from the node n to the node o)/h(n)     (2)

If roads are distributed uniformly, the weighting factor k of theheuristic term h(n) can generally be supposed to have an almost constantvalue independent of the node n. FIG. 10 is a diagram showing thetransition of the extent of searching in case of performing thesearching from the node s of a starting point to the node o of adestination by using the value of k as a parameter when the values of kat every node in the extent of searching are supposed to be constant. Asapparent from the figure, the extent of searching becomes wider inaccordance with the increasing of the values of the weighting factor kof the heuristic term h(n), and the efficiency of the searching becomesworse.

When k=1, the heuristic term or the estimated cost completely agreeswith the actual cost, and only the nodes on the optimal routes are theobjects to be searched. In this case, the efficiency of searchingbecomes maximum. On the other hand, when k=∞, the extent of searching isthe same as that in case of having no heuristic term and becomes acircle having a center point of node s of a stating point.

In real roads, the length of routes is about one time to one and a halftimes as long as the length of straight lines except for special casessuch as ones between the summit of a mountain and the foot of themountain, ones on a shore of a bay, and the like.

A route having the minimum length is ordinarily obtained as an optimalroute, but the route having the minimum length is not always the optimalroute simply in actual roads, and searching must be performed withregard for the ease of driving. Accordingly, a more practical optimalroute is required to be searched by regarding the link lengths of anarrow road as ones longer than real lengths, and defining the lengthper turn to the right or to the left to convert turns to lengths to beadded to the cost, or the like. In those cases, g(n) becomes larger thanthat in case of regarding only the lengths of routes.

For example, it is supposed that the length of a link is multiplied bythe following factors in accordance with the number of traffic lanes sothat broad roads are given priority to be traveled by cars.

Two or more lanes on one side: one time,

One lane on one side: two times,

Narrow streets: four times.

In this case, g(n) surely becomes double or more in a search in adistrict in which there is no road having two or more lanes on one side.Almost all arterial roads, other than express-highways, applied to asearch of long distance have many sections having one lane on one side,and have sections having two or more lanes on one side only around bigcities. Therefore, g(n) is greatly increased also in a search of longdistance applied to the roads of the level of arterial roads.

On the other hand, for keeping the optimality of routes, h(n) isrequired to be always smaller than the actual cost from the node n tothe node o of a destination. In a search in which a road having twolanes on one side becomes the optimal route, since the size of g(n) doesnot vary in accordance with the length of routes, h(n) can not be largerthan the distance of a straight line for keeping the optimality.Consequently, in a search in which a road having one lane on one side isthe optimal route, the value of the weighting factor k of a heuristicterm also increases in proportion to g(n), and the extent and the timeof searching also increase.

Since there is no need to obtain a strictly optimal route but it isenough to obtain a quasi-optimal route sufficient for guiding a driverin route-searching, it is a practical technique to shorten the time ofsearching by increasing h(n) to the extent of not worsening thequalities of routes. In case of practicing a search using a hierarchicalmap, there are many cases where the length of a link is much longer thanthe distance of a straight line between nodes because in an upper rankeddigital map data including only arterial roads one link includes manyintersections and curves in a lower ranked digital map data.Consequently, the optimality is not easy to be decreased even if h(n) issomewhat increased. Besides, since all roads are arterial roads, it iseasy to obtain good routes even if the optimal route cannot be obtained.

But, in digital map data ranked in a lower rank from a starting point toan arterial road or from an arterial road to a destination, there aresome cases where the total cost becomes smaller by, for exampletravelling away from the destination to get to an arterial road, or bytraveling through a much farther arterial road instead of travelingthrough a nearby arterial road. Consequently, there is a case where anapparently strange route is searched, if the optimality is not ensured.Since links are divided to be short, there are little difference betweenthe length of links and the distance of a straight line between nodes,and then increasing h(n) is apt to decrease the optimality.

Since the conventional in-car navigation apparatus is constructed asdescribed above, the apparatus obtains the heuristic term h(n) of anevaluation function by means of a uniform formula in every rank of adigital map data having a hierarchical construction. Consequently, ithas a problem that it is difficult to shorten the time of searchingwhile the qualities of routes are maintained.

SUMMARY OF THE INVENTION

In view of the foregoing, it is an object of the present invention toprovide an in-car navigation apparatus capable of searching an optimalor a quasi-optimal route always, and capable of shortening the waitingtime for obtaining a route.

It is another object of the present invention to provide an in-carnavigation apparatus capable of setting the conditions of searching aroad through which a car should pass, and capable of searching always anoptimal or a quasi-optimal route in conformity with set conditions.

It is a further object of the present invention to provide an in-carnavigation apparatus capable of setting searching conditions of whethera user gives priority to computing time necessary for searching orwhether the user gives priority to the searching of the optimal route,and always capable of searching the optimal or a quasi-optimal route inconformity with set conditions.

According to the first aspect of the present invention, for achievingthe above-mentioned objects, there is provided an in-car navigationapparatus comprising a searching means for searching a route from anappointed starting point to a destination through which a moving bodysuch as a car should travel by means of a heuristic algorithm bychanging a weight of a heuristic term of an evaluation function or theevaluation function itself in accordance with the ranks of digital mapdata stored in a map database means.

As stated above, in the in-car navigation apparatus according to thefirst aspect of the present invention, the searching means thereofsearches a route from an appointed starting point to a destinationthrough which a moving body such as a car should travel by means of aheuristic algorithm by changing a weight of a heuristic term of anevaluation function or the evaluation function itself in accordance withthe ranks of digital map data stored in a map database means.Specifically, since the in-car navigation apparatus performs ahigh-speed searching in arterial roads which are almost all parts of aroute and scarcely worsened in quality, and performs a searching withkeeping the optimality of a route in the neighborhoods of a startingpoint and a destination which are extremely small parts of a route buteasy to be worsened in quality, it is enabled that the qualities ofroutes are maintained while the time of searching is greatly shortened.

According to the second aspect of the present invention, there isprovided an in-car navigation apparatus wherein the searching meansthereof searches a route by making the weight of a heuristic termsmaller in accordance with the largeness of the detail of a road in arank of a digital map data.

As stated above, in the in-car navigation apparatus according to thesecond aspect of the present invention, the searching means thereofsearches a route by making the weight of a heuristic term smaller inaccordance with the largeness of the detail of a road in a rank of adigital map data. Consequently, it is enabled that the qualities ofroutes are maintained while the time of searching is greatly shortenedsimilarly to the first aspect.

According to the third aspect of the present invention, there isprovided an in-car navigation apparatus wherein the digital map datathereof is composed of a first rank including only major arterial roadssuch as an express-highway and the like, a second rank including roadsmajor to local arterial roads inclusive, and a third rank including allroads through which general moving bodies can pass, and wherein thesearching means thereof searches routes in consecutive order in eachrank by decreasing the weight of the heuristic term of an evaluationfunction in the order from the first rank to the third rank.

As stated above, in the in-car navigation apparatus according to thethird aspect of the present invention, the searching means thereofsearches routes in consecutive order in each rank by decreasing theweight of the heuristic term of a synthetic evaluation function in theorder of a first rank including only major arterial roads such as anexpress-highway and the like, a second rank including major and localarterial roads inclusive, and a third rank including all roads throughwhich general moving bodies can pass. Consequently, it is enabled thatthe qualities of routes are maintained while the time of searching isgreatly shortened.

According to the fourth aspect of the present invention, there isprovided an in-car navigation apparatus wherein the searching meansthereof selects a rank of a digital map data from which searching isbegun in accordance with the distance of a straight line from anappointed starting point to a destination.

As stated above, in the in-car navigation apparatus according to thefourth aspect of the present invention, the searching means thereofselects a rank of a digital map data from which searching is begun inaccordance with the distance of a straight line from an appointedstarting point to a destination. Specifically, it is preferable tosearch arterial roads in the second rank or search routes only in thethird rank if the starting point and the destination are near. Thereby,the computing time required for searching can be shortened, andeffective searching can rapidly be performed.

According to the fifth aspect of the present invention, there isprovided an in-car navigation apparatus wherein the searching meansthereof changes the weight of a heuristic term of an evaluation functionor the evaluation function itself in conformity with searchingconditions, which are set by a user, of a road through which a movingbody should travel.

As stated above, in the in-car navigation apparatus according to thefifth aspect of the present invention, since the searching means thereofchanges the weight of a heuristic term of an evaluation function or theevaluation function itself in conformity with searching conditions,which are set by a user of a road through which a moving body shouldtravel, both of the keeping of the quasi-optimality of a route and theshortening of the time of searching are compatible.

According to the sixth aspect of the present invention, there isprovided an in-car navigation apparatus wherein the searching meansthereof changes the weight of a heuristic term of an evaluation functionor the evaluation function itself in conformity with searchingconditions, which are set by a user, of whether the computing timenecessary for searching is given priority or whether the searching of anoptimal route is given priority.

As stated above, in the in-car navigation apparatus according to thesixth aspect of the present invention, the searching means thereofchanges the weight of a heuristic term of an evaluation function or theevaluation function itself in conformity with searching conditions,which are set by a user, of whether the computing time necessary forsearching is given priority or whether the searching of an optimal routeis given priority. Specifically, if a user attaches importance to theoptimality of routes, the in-car navigation apparatus ensures theoptimality of routes by decreasing the weight of the heuristic term; ifthe user attaches importance to the speed of searching, the apparatuscan make the speed of searching fast by making the heuristic termweighted greater. Thereby, the apparatus can always search an optimal ora quasi-optimal route in response to the request of a user, and furtherit can shorten the time of waiting until routes are obtained.

BRIEF DESCRIPTION OF THE DRAWINGS

Further objects and advantages of the present invention can be morefully understood from the following detailed description taken inconjunction with the accompanying drawings, in which:

FIG. 1 is a block diagram showing the construction of the in-carnavigation apparatus according to an embodiment of the presentinvention;

FIG. 2 is a diagram showing a tentative starting point and a tentativedestination set on the digital map data of rank 2, and route to besearched at the rank 2 in the navigation apparatus shown in FIG. 1;

FIG. 3 is a diagram showing a tentative starting point set on thedigital map data of rank 1 and route to be searched at the rank 1 on thestarting point side in the navigation apparatus shown in FIG. 1;

FIG. 4 is a diagram showing routes to be searched of rank 0 on thestarting point side in the navigation apparatus shown in FIG. 1;

FIG. 5 is a flow chart showing an example of the processes ofroute-searching by using digital map data having a hierarchyconstruction in the in-car navigation apparatus shown in FIG. 1;

FIG. 6 is a flow chart showing an example of the processes ofroute-searching by using digital map data having a hierarchyconstruction in the in-car navigation apparatus according to anotherembodiment of the present invention;

FIG. 7 is a view showing a picture for setting the conditions ofsearching displayed on the displaying section of the in-car navigationapparatus according to the embodiment shown in FIG. 6;

FIG. 8 is a view showing a picture for setting the conditions ofsearching displayed on the displaying section of the in-car navigationapparatus according to further embodiment of the present invention:

FIG. 9 is a block diagram showing the construction of a conventionalin-car navigation apparatus; and

FIG. 10 is a diagram notionally showing the transition of the extent ofsearching in the case where the weight of cost in heuristic searching.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Preferred embodiments of the present invention will now be described indetail with reference to the accompanying drawings.

Embodiment 1

FIG. 1 is a block diagram showing the construction of the in-carnavigation apparatus according to a first embodiment of the presentinvention. In figures, the same reference characters denote the same orequivalent parts, and thus their description will not be repeated.Reference numeral 6 denotes a function computing section provided in theoperating section 4 and computing evaluation functions forroute-searching in accordance with the ranks of digital map data.Reference numeral 7 denotes a factor determining section for setting thevalues of each factor to be used in a formula for the use of thecomputations of the evaluation functions of the function computingsection 6. Reference numeral 8 denotes a condition judging section forinforming the conditions for the determination of the weighting factorsof a heuristic term h(n) of the faction determining section 7.

In operation, when a user appoints a starting point and a destination ofroute-searching with the handling section 3, and further when the userrequests an optimal route after he set searching conditions of, forexample whether toll roads are used or not, the handling section 3requires the searching of an optimal route by informing the set contentsto the operating section 4. The operating section reads in digital mapdata in necessary areas from the map database section 2, and searches aroute by means of a heuristic algorithm so that the cost of the routefrom a starting point to a destination becomes almost minimum forsending the searched route to the displaying section 5. At this time,the function computing section 6 computes evaluation functions of eachnode by using the weighting factor of the heuristic term h(n) set byfactor determining section 7. The displaying section 5 informs a user ofan optimal route to a destination by displaying roads along the optimalroute output from the operating section 4 with a special color, and soforth.

The digital map data stored in the map database section 2 have ahierarchy construction to be divided into a high level rank includingonly arterial roads and a low level rank including minute roads. In thecase where the operating section 4 searches an optimal route in responseto a request of a user, at first the operating section 4 searches routesfrom an arterial road near to the node s of a starting point to anarterial road near to the node o of a destination by means of thedigital map data in the high level rank, then searches a route from thenode s of the starting point to an arterial road and a route from anarterial road to the node o of the destination by means of the digitalmap data in the low level rank.

According to the present embodiment, the evaluation function f(n) of thenode n is obtained by means of the following formula when routes aresearched in each rank of the digital map data.

    f(n)=g(n)+k.sub.h ×h(n)                              (3)

where k_(h) is a weighting factor of the heuristic term h(n) which isdefined for every rank of the digital map data.

As shown in FIG. 2, the digital map data of an area including the node sof the starting point through the node o of the destination among thedigital map data in the rank 2 including only national roads andexpress-highways are read out from the map database section 2, and alink nearest to the node s of the starting point among the linksincluded in the rank 2 is selected to define the node nearer to the nodes of the starting point between the nodes of both ends of the selectedlink as a tentative node s₂ of the starting point. Also, a link nearestto the node o of the destination is selected, and the node nearer to thenode o of the destination between the nodes of both ends of the selectedlink is defined as a tentative node o₂ of the destination to search theroute from the tentative node s₂ of the starting point to the tentativenode o₂ of the destination in the digital map data in the rank 2. Atthat time, the evaluation function f(n) is computed in the conditionthat the weighting factor k_(h) of the heuristic term h(n) in theformula (3) is set as a proper value k_(h2) in the rank 2.

Next, as shown in FIG. 3, the digital map data in an area including thenode s of the starting point through the tentative node s₂ of thestarting point among the digital map data in the rank 1 including majorand local arterial roads inclusive are read out from the map databasesection 2, and a link nearest to the node s of the starting point amongthe links included in the rank 1 is selected to define the node nearerto the node s of the starting point between the nodes of both ends ofthe selected link as a tentative node s₁ of the starting point forsearching a route from the tentative node s₁ of the starting point tothe tentative node s₂ of the starting point in the digital map data inthe rank 1. On that occasion, the evaluation function is computed in thecondition that the weighting factor k_(h) of the heuristic term h(n) inthe formula (3) is set as a value k_(h1) for rank 1.

Moreover, as shown in FIG. 4, the digital map data in an area includingthe node s of the starting point through the tentative node s₁ of thestarting point among the digital map data in the rank 0 including allroads through which general cars can pass are read out from the mapdatabase section 2 to search routes from the node s of the startingpoint to the tentative node s₁ of the starting point in the digital mapdata in the rank 0. On that occasion, the evaluation function iscomputed in the condition that the weighting factor k_(h) of theheuristic term h(n) in the formula (3) is set as a value k_(h0) to therank 0.

On the destination side, similarly on the starting point side, routesare searched from a tentative node o₂ of the destination to a tentativenode o₁ of the destination in the digital map data in the rank 1, androutes are searched from the tentative node o₁ of the destination to thenode o of the destination in the digital map data in the rank 0.

In the aforementioned searching by means of ranks, supposing that, forexample k_(h2) =2.0, k_(h1) =1.5, k_(h0) =1.0, searching is performed bymeans of the high-speed algorithm A in the route in the rank 2 ofarterial lines where the optimality is easily maintained, and isperformed by means of the algorithm A*, which can ensure the optimalityin the routes in the rank 0 around the node s of the starting point orthe node o of the destination where the sections are short but theoptimally is difficult to maintain.

Although searching is performed from the rank 2 in the aforementionedexample, if the node s of a starting point and the node o of adestination are near, it is preferable to search arterial roads in therank 1 or search by means of only the rank 0. Even in these cases,values set to every rank in accordance with rank levels are used as thevalue of the weighting factor k_(h) of the heuristic term h(n) used inthe evaluation function formula (3).

FIG. 5 is a flow chart showing the processes of route-searching in thein-car navigation apparatus in case of changing the ranks of digital mapdata to be searched in accordance with the distance of a straight linebetween the node s of a starting point and the node o of a destination.At step ST1, the distance L of a straight line between the node s of astarting point and the node o of a destination is obtained. At step ST2,a rank level p_(max) to be used for searching arterial roads isdetermined in accordance with the distance L of a straight line. At stepST3, a tentative node s' of the starting point and a tentative node o'of the destination are determined in the digital map data in the rank ofthe rank level p_(max). At step ST4, arterial routes (not alwaysarterial roads) from the tentative node s' of the starting point to thetentative node o' of the destination are searched by means of the valueof the weighting factor k_(h) corresponding to the rank level p_(max).If the rank level p_(max) is equal to 0, the searching is finished atstep ST5; if the rank level p_(max) is 1 or more, low rank routes on thestarting point side are searched in order from the rank level (p_(max)-1) to the rank level 0 at step ST6 through step ST10, and low rankroutes on the destination side are searched in order from the rank level(p_(max) -1) to the rank level 0 at step ST11 through step ST15.

As an alternate example of the present embodiment, g(n) may bemultiplied by the inverse number of the weighting factor k_(h) insteadof the heuristic term h(n) being multiplied by the weighting factork_(h) in the evaluation function formula (3). In this case also,advantages similar to those of the embodiment can be obtained. Theevaluation function formula (3) is changed to:

    f(n)=g(n)/k.sub.h +h(n)                                    (4).

In this case also, routes are searched by varying the values of theweighting factor k_(h) of the heuristic term h(n) in accordance with theranks of the digital map data. The effects of the weighting factor k_(h)to the extent of searching is the same as those of the weighting factork_(h) in the formula (3).

Alternatively, the weighting of the heuristic term may be varied byvarying the formula of h(n) itself for each rank instead of multiplyingh(n) by the weighting factors. Ordinarily, h(n) can be obtained by thefollowing formula.

    h(n)= x(n).sup.2 +y(n).sup.2 !.sup.1/2                     (5)

where x(n) is a distance in the longitudinal direction from the node nto the node o of a destination, and y(n) is a distance in thelatitudinal direction from the node n to the node o of the destination.In, for example, the high level rank in the digital map data, theheuristic term h(n) is computed by altering the formula (5) into thefollowing formula.

    h(n)=x(n)+y(n)                                             (6)

Since the values obtained by the formula (6) are always the valuesobtained by the formula (5) or more, the weight of the heuristic termbecomes larger in the high level rank of the digital map data inconformity with this method.

As described above, according to the present embodiment, in case ofsearching routes form a starting point to a destination by means of theheuristic algorithm on the basis of digital map data having a hierarchyfor each rank to be searched by the alteration of the factor thereof orthe alteration of the computing formula itself of the heuristic term tomake the heuristic term weighted greater making the speed of searchingfaster in case of sections where quasi-optimal routes are easy to beobtained. Thereby, there can be obtained the advantage that an optimalor a quasi-optimal route can always be searched, and further waitingtime for obtaining routes is shortened.

Embodiment 2

FIG. 6 is a flow chart showing the processes of route-searching in thein-car navigation apparatus according to a second embodiment of thepresent invention. According to the embodiment, the in-car navigationapparatus is constructed not only to change the heuristic term for eachrank of the digital map data, but also to change it in accordance withthe set conditions for searching.

For example, a searching condition whether toll roads have priority tobe used or not is considered. If toll roads have priority to be used, itis necessary to travel through free roads up to an interchange(hereinafter referred to as I.C.), and there are some cases where thecar temporarily goes through a free road when it changes toll roads. Iftoll roads have no priority to be used, there are some cases where adestination is set on an island where the car is obliged to pass througha toll bridge; in such cases the algorithm of the in-car navigationapparatus cannot avoid using a toll road. Accordingly, there is used amethod in which searching is performed by means of the evaluationfunction which multiplies the free link length by a large factor if tollroads have priority to be used, and multiplies the toll link length by alarge factor if toll roads have no priority to be used.

Since there are many toll roads, especially express-highways, which havetwo traffic lanes or more on one side and have no signals, indicatorsfor turning right or left, or the like, the value of g(n) is not soincreased in comparison with the length of routes if routes are set inthe condition of giving priority to toll roads. Also, since the in-carnavigation apparatus does not trace the node on free roads, but tracesthe nodes on toll roads, if a toll road once entered the extent ofsearching, the time of searching becomes shorter than that in case ofnot giving priority to toll roads. Consequently, in case of givingpriority to toll roads, the necessity for shortening the time ofsearching with the sacrifice of the optimality is less in comparisonwith the case where toll roads have no priority.

On the other hand, if toll roads have priority to be searched, sincetoll roads have the road densities of road networks far smaller thanthose of free roads, a user has a large sense of incompatibility if theapparatus selects a wrong toll road or a route having no toll road.There are some cases where a route from a starting point to an I.C.greatly turns aside from the direction of a destination, and the degreeof the demand of the optimality is consequently higher than that in thecase where toll roads have no priority.

Therefore, if searching is performed in the searching condition thattoll roads have priority, it is preferable to perform the searchinghaving higher optimality by making the weight of the heuristic term lessthan that in the case where toll roads have no priority. For example,the value of the weighting factor k_(h) of the heuristic term h(n) inthe evaluation function formula (3) is changed in accordance with notonly the rank levels of the digital map data, but also searchingconditions of whether toll roads have or have not priority, and set asfollows:

(1) in case of giving no priority to toll roads:

    k.sub.h0 =1.0, k.sub.h1 =1.5, k.sub.h2 =2.0

(2) in case of giving priority to toll roads:

    k.sub.h0 =1.0, k.sub.h1 =1.2, k.sub.h2 =1.5.

By changing the weight of the heuristic term in accordance with thesearching conditions as described above, the compatibility between themaintenance of the quasi-optimality of routes and the shortening of thesearching time can be realized. Other searching conditions such aswhether other broad roads have priority or not, whether turning to rightor left is evaded or not, or the like are conceivable, and accordingly,by setting the weight of the heuristic term appropriately to eachcombination of those searching conditions, the compatibility between themaintenance of the quasi-optimality of routes and the shortening of thesearching time can always be realized.

Whether broad roads have priority or not is set as a searchingcondition, since it is required to travel through selected broad roadseven if they are somewhat roundabout routes in the case where broadroads have priority, it is needed to perform the search having higheroptimality. If whether turning to right or left is to be evaded or notis set as a searching condition, since it is needed to add supposeddistances of several hundreds meters per turn to right or left to thecost of routes in case of evading turning to right or left, theoptimality higher than that in case of not evading turning to right orleft is requested. Accordingly, the weighting factors of the heuristicterm h(n) are set as follows, for example:

(1) in case of giving priority to broad roads:

    k.sub.h0 =1.0, k.sub.h1 =1.2, k.sub.h2 =1.5

(2) in case of giving no priority to broad roads:

    k.sub.h0 =1.0, k.sub.h1 =1.5, k.sub.h2 =2.0

(3) in case of evading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.4, k.sub.h2 =1.8

(4) in case of not evading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.5, k.sub.h2 =2.0.

If there are a plurality of searching conditions, weighting factorspreviously may be prepared for every combination of searching conditionsfor reading in from a table. If the number of searching conditions islarge, weighting factors may be produced before searching by multiplyingweighting factors to each searching condition together, or by addingthem up. For example, if there are three searching conditions of whethertoll roads have priority or not, whether broad roads have priority ornot, and whether turning right or left is evaded or not, for example thefollowing weighting factors are prepared for each one of eightcombinations of searching conditions in total, if weight factors arepreviously prepared.

(1) in case of giving priority to toll roads and broad roads, andevading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.1, k.sub.h2 =1.3

(2) in case of giving priority to toll roads and broad roads, and notevading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.2, k.sub.h2 =1.4

(3) in case of giving priority to toll roads, giving no priority tobroad road, and evading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.2, k.sub.h2 =1.5

(4) in case of giving priority to toll roads, giving no priority tobroad road, and not evading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.3, k.sub.h2 =1.6

(5) in case of giving no priority to toll roads, giving priority tobroad road, and evading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.3, k.sub.h2 =1.7

(6) in case of giving no priority to toll roads, giving priority tobroad road, and not evading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.4, k.sub.h2 =1.8

(7) in case of giving no priority to toll roads and broad road, andevading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.4, k.sub.h2 =1.9

(8) in case of giving no priority to toll roads and broad road, and notevading turning right or left:

    k.sub.h0 =1.0, k.sub.h1 =1.5, k.sub.h2 =2.0.

On the other hand, there is also a method in which weighting factors areobtained in every rank of digital map data by adding up each weightingfactor previously set to each searching condition, for example as shownin follows, in accordance with searching conditions.

(1) reference factors to be bases of weighting factors in every rank ofdigital map data:

    k.sub.h0A =1.0, k.sub.h1A =1.1, k.sub.h2A =1.3

(2) in case of giving priority to toll roads:

    k.sub.h0B =0.0, k.sub.h1B =0.0, k.sub.h2B =0.0

(3) in case of giving no priority to toll roads:

    k.sub.h0B =0.0, k.sub.h1B =0.2, k.sub.h2B =0.4

(4) in case of giving priority to broad roads:

    k.sub.h0C =0.0, k.sub.h1C =0.0, k.sub.h2C =0.0

(5) in case of giving no priority to broad roads:

    k.sub.h0C =0.0, k.sub.h1C =0.1, k.sub.h2C =0.2

(6) in case of evading turning right or left:

    k.sub.h0D =0.0, k.sub.h1D =0.0, k.sub.h2D =0.0

(7) in case of not evading turning right or left:

    k.sub.h0D =0.0, k.sub.h1D =0.1, k.sub.h2D =0.1

Accordingly, weighting factors are computed for each rank of the digitalmap data in conformity with the following formula.

    k.sub.h0 =k.sub.h0A +k.sub.h0B +k.sub.h0C +k.sub.h0D

    k.sub.h1 =k.sub.h1A +k.sub.h1B +k.sub.h1C +k.sub.h1D

    k.sub.h2 =k.sub.h2A +k.sub.h2B +k.sub.h2C +k.sub.h2D

Next, the operation of the embodiment will be described. Hereinafter, asto the case where the aforementioned three searching conditions can beset by combining each other, the processes of the route-searching of thein-car navigation apparatus of the embodiment will be described.

FIG. 7 is a view showing a picture for setting the conditions ofsearching displayed on the displaying section 5. A user sets threesearching conditions shown in FIG. 7 by handling the handling section 3.In the example shown in FIG. 7, there is set a searching condition inwhich toll roads have no priority, broad roads have priority, andturning right or left is evaded. As shown in the flow chart of FIG. 6,at step ST21, searching conditions are at first judged for judging thesearching condition out of the aforementioned eight types ofcombinations. Next, at step ST22, weighting factors of the heuristicterm k_(h0) -k_(h2) in the three ranks of the digital map data are set.

After the weighting factors were set, at step ST23, the distance L of astraight line between the node s of a starting point and the node o of adestination is obtained. At step ST24, a rank level p_(max) to be usedfor searching arterial roads is determined in accordance with thedistance L of a straight line. Next, at step ST25, a tentative node s'of the starting point and a tentative node o' of the destination aredetermined in the digital map data in the rank of the rank levelp_(max). At step ST26, arterial routes (not always arterial roads) fromthe tentative node s' of the starting point to the tentative node o' ofthe destination are searched by means of the value of the weightingfactor k_(h) corresponding to the rank level p_(max). If the rank levelp_(max) is equal to 0, the searching is finished at step ST27; if therank level p_(max) is 1 or more, lower rank routes on the starting pointside are searched in order from the rank level (p_(max) -1) to the ranklevel 0 at step ST28 through step ST32, and lower rank routes on thedestination side are searched in order from the rank level (p_(max) -1)to the rank level 0 at step ST33 through step ST37.

Not only by varying the weighting factor of the heuristic term to everyrank, but also by varying the heuristic term in accordance withsearching conditions as shown in the aforementioned examples, it is madeto be possible to shorten the searching time effectively while keepingthe optimality of routes.

Embodiment 3

FIG. 8 is a view showing a picture for setting the conditions ofsearching in the in-car navigation apparatus according to a thirdembodiment of the present invention. In the figure, reference numeral 20denotes items for setting the searching conditions related to the natureof route-searching.

In operation, the processes of route-searching can be executed inconformity with the flow chart shown in FIG. 6 in this embodiment, too.Although conditions of roads to be travelled are set as searchingconditions, and the operating section 4 automatically sets the weightingfactor of the heuristic term in the aforementioned embodiment 2, byadding the selection of whether the speed of searching is attachedimportance or whether the optimality of routes is attached importance,as shown in FIG. 8, and by changing the value of the weighting factork_(h) of the heuristic term in accordance with whether speed oroptimality is attached importance, the weight of the heuristic term canalso be changed in accordance with the preference of a user.

For example, if the user select "OPTIMAL ROUTE", which attachesimportance to the optimality, all of the weighting factors k_(h0)-k_(h2) of the heuristic term in the aforementioned three ranks of thedigital map data shown in the embodiment 1 are 1.0. If the user select"ORDINARY", the weighting factors k_(h0) -k_(h2) of the heuristic termare equal to the weighting factors of the heuristic term in any one caseof the eight types of the combinations of three searching conditionsshown in the aforementioned embodiment 2; if the user select "HIGH-SPEEDSEARCHING", which attaches importance to the speed of searching, theweighting factors k_(h0) -k_(h2) of the heuristic term are equal to oneand half times as large as the weighting factors of the heuristic termfor each of the eight types of the combinations of three searchingconditions shown in the aforementioned embodiment 2.

If re-searching is requested for the routes searched with attachingimportance to speed, it is preferable to automatically change thesearching condition to one which attaches importance to the optimality.

As described above, according to the present embodiment, when routesfrom a starting point to a destination are searched by means of theheuristic algorithm on the basis of the digital map data having ahierarchy construction, the weight of the heuristic term is varied byaltering the weight of the heuristic term by the alteration of factorsor the computing formula of the heuristic term itself in conformity withthe set searching conditions, for ensuring the optimality of routes bymaking the weight of the heuristic term less in case of attachingimportance to the optimality of routes, and for making the weight of theheuristic term greater to make searching speed faster in case ofattaching importance to the searching speed. Thereby, the embodiment hasan advantage that an optimal or a quasi-optimal route can always besearched in response to the request of a user, and further that waitingtime for obtaining routes is shortened.

It will be appreciated from the foregoing description that, according tothe first aspect of the present invention, the in-car navigationapparatus is constructed to comprise a searching means for searching aroute from an appointed starting point to a destination through which amoving body such as a car should travel by means of a heuristicalgorithm by changing the weight of a heuristic term of an evaluationfunction or the evaluation function itself in accordance with the ranksof digital map data stored in a map database means, and consequently,the in-car navigation apparatus ensures the optimality of routes bymaking the heuristic term less where the optimality of routes isattached importance, and can make the searching speed faster by makingthe heuristic term less where quasi-optimal routes are easy to beobtained, thereby the apparatus has an advantage that the optimal or aquasi-optimal route can always be searched, and further that waitingtime for obtaining routes can be shortened.

Furthermore, according to the second aspect of the present invention,the in-car navigation apparatus is constructed so that the searchingmeans thereof searches a route by making the weight of a heuristic termless in accordance with the largeness of detail of a road in a rank of adigital map data, and consequently, the apparatus has an advantage thatthe qualities of routes can be maintained while the time of searching isgreatly shortened.

Furthermore, according to the third aspect of the present invention, thein-car navigation apparatus is constructed so that the digital map datathereof is composed of a first rank including only major arterial roadssuch as an express-highway and the like, a second rank including roadsmajor and local arterial roads inclusive, and a third rank including allroads through which general moving bodies can pass, and that thesearching means thereof searches routes in consecutive order in eachrank by decreasing the weight of the heuristic term of an evaluationfunction in the order from the first rank to the third rank, andconsequently, the apparatus has an advantage that the qualities ofroutes can be maintained while the time of searching is greatlyshortened.

Furthermore, according to the fourth aspect of the present invention,the in-car navigation apparatus is constructed so that the searchingmeans thereof selects a rank of a digital map data from which searchingis begun in accordance with the distance of a straight line from anappointed starting point to a destination, and consequently, theapparatus has an advantage that the computing time required forsearching can be shortened, and that effective searching can rapidly beperformed.

Furthermore, according to the fifth aspect of the present invention, thein-car navigation apparatus is constructed so that the searching meansthereof changes the weight of a heuristic term of an evaluation functionor the evaluation function itself in conformity with searchingconditions, which are set by a user, of a road through which a movingbody should travel, and consequently, the in-car navigation apparatusensures the optimality of routes by making the heuristic term less whenthe optimality of routes is attached importance, and can make thesearching speed faster by making the heuristic term more whenquasi-optimal routes are easy to be obtained, thereby the apparatus hasan advantage that the optimal or a quasi-optimal route can always besearched, and further that waiting time for obtaining routes can beshortened.

Furthermore, according to the sixth aspect of the present invention, thein-car navigation apparatus is constructed so that the searching meansthereof changes the weight of a heuristic term of an evaluation functionor the evaluation function itself in conformity with searchingconditions, which are set by a user, of whether the computing timenecessary for searching is given priority or whether the searching of anoptimal route is given priority, and consequently, the apparatus canalways search an optimal or a quasi-optimal route in response to thepreference or a request of a user, and further it can shorten the timeof waiting until the route is obtained.

While preferred embodiments of the present invention have been describedusing specific terms, such description is for illustrative purposesonly, and it is to be understood that changes and variations may be madewithout departing from the spirit or scope of the following claims.

What is claimed is:
 1. An in-car navigation apparatus comprising:a mapdatabase storing digital map data composed of at least two ranksdifferent in degree of road detail; and searching means for searching aroute from an appointed starting point to a destination through which amoving body should travel by means of a heuristic algorithm by changinga relative weight of a heuristic term of an evaluation function inaccordance with said ranks of the digital map data stored in said mapdatabase.
 2. A navigation system for determining a route to be travelledby a moving body going from starting point S to destination point T,comprising:a map database containing a plurality of maps havingdifferent rank numbers; and an operating section for selecting one ofsaid ranked maps from said map database and for determining a section ofsaid route from point S to point T by calculating an evaluation valuefrom an evaluation function f(n), said evaluation function f(n)including a calculated cost term g(n) and a heuristic term h(n), theweight of said heuristic term h(n) relative to said calculated cost termg(n) being set in accordance with the rank number of said selected map.3. A navigation system according to claim 2, wherein said operatingsection changes the weight of the heuristic term h(n) relative to thecost term g(n) in conformity with searching conditions regarding a roadtype through which the moving body should travel.
 4. A navigation systemaccording to claim 2, wherein said operating section changes the weightof the heuristic term h(n) relative to the cost term g(n) in conformitywith searching conditions regarding whether computing time necessary forsearching is given priority or whether searching of an optimal route isgiven priority.
 5. A navigation system according to claim 2, whereinsaid operating section selects a rank of map data from which searchingis begun in accordance with a distance of a straight line from theappointed starting point S to the destination point T.
 6. A navigationsystem according to claim 2, wherein said map data stored in said mapdatabase is composed of a first rank including only major arterialroads, a second rank including major and local arterial roads, and athird rank including all passable roads, and wherein said operatingsection searches routes in consecutive rank order by decreasing theweight of the heuristic term h(n) relative to the cost term g(n) inorder from the first rank to the third rank.
 7. A navigation systemaccording to claim 2, wherein said operating section searches a route bymaking the weight of the heuristic term h(n) relative to the cost termg(n) small in accordance with largeness of detail of a road in a rank ofthe map data.
 8. A navigation system as defined in claim 2, wherein theweight of said heuristic term h(n) relative to said cost term g(n) isset by multiplying h(n) by a weighting factor k_(h) which changes fordifferent map rank numbers.
 9. A navigation system as defined in claim2, wherein the weight of said heuristic term h(n) relative to said costterm g(n) is set by multiplying said cost term g(n) by the inverse of aweighting factor k_(h) which changes for different map rank numbers. 10.A navigation system as defined in claim 2, wherein the weight of saidheuristic term h(n) relative to said cost term g(n) is set bycalculating h(n) with a formula which changes for different map ranknumbers.
 11. A navigation system as defined in claim 2, wherein saidoperating section changes the weight of said heuristic term h(n)relative to said cost term g(n) in conformity with a searchingcondition, said searching condition including an indication that tollroads are or are not preferred.
 12. A navigation system as defined inclaim 2, wherein said operating section changes the weight of saidheuristic term h(n) relative to said cost term g(n) in conformity with asearching condition, said searching condition including an indicationthat wide roads are or are not preferred.
 13. A method for navigating aroute to be travelled by a moving body going from starting point S todestination point T, comprising the steps of:(a) storing in a database aplurality of maps having different rank numbers; (b) selecting one ofsaid ranked maps from said map database; (c) determining a section ofsaid route from point S to point T by calculating an evaluation valuefrom an evaluation function f(n), said evaluation function f(n)including a calculated cost term g n) and a heuristic term h(n), theweight of said heuristic term h(n) relative to said calculated cost termg(n) being set in accordance with the rank number of said selected map;and (d) repeating said steps (b) and (c) until a desirable completeroute from point S to point T is determined.
 14. A method for navigatingas defined in claim 13, wherein the weight of said heuristic term h(n)relative to said cost term g(n) is set by multiplying h(n) by aweighting factor k_(h) which changes for different map rank numbers. 15.A method for navigating as defined in claim 13, wherein the weight ofsaid heuristic term h(n) relative to said cost term g(n) is further setin accordance with whether computing time or the determination of anoptimal route is given priority.
 16. A method for navigating as definedin claim 13, wherein the rank of the map initially selected in step (b)is determined in accordance with the distance of a straight line formstarting point S to destination point T.
 17. A method for navigating asdefined in claim 13, wherein the weight of said heuristic term h(n)relative to said cost term g(n) is further set in accordance with aselected road type preference.
 18. A method for navigating as defined inclaim 13, wherein the weight of said heuristic term h(n) relative tosaid cost term g(n) is further set in accordance with the level of roaddetail.
 19. A method for navigating as defined in claim 13, wherein saidranked maps includes; a map having a high rank which contains only majorarterial roads, a map having an intermediate rank which contains bothmajor and local arterial roads, and a map having a low rank whichincludes all passable roads, said steps (b) and (c) starting with a highranked map and progressing consecutively through lower ranked maps untila desirable complete route from starting point S to destination point Tis determined, the weight of said heuristic term h(n) relative to saidcost term g(n) decreasing with a decrease in map rank.